All Topics
Computer programming and development are critical to the past, present, and future of geospatial systems and techniques. The increasing ubiquity and diversity of online, mobile, and desktop GIS platforms along with the inclusion of cyber-infrastructure components within the bounds of geographic information systems (e.g., supercomputing, wireless sensor networks) means that GIS researchers and professionals need to be fluent in multiple forms of programming, and the life-cycles of system and software development.
Topics in this Knowledge Area are listed thematically below. Existing topics are in regular font and linked directly to their original entries (published in 2006; these contain only Learning Objectives). Entries that have been updated and expanded are in bold. Forthcoming, future topics are italicized.
| Algorithm Design/Algorithmic Approaches | Programming Languages & Libraries |
| Real-time GIS Programming and Geocomputation | Python for GIS |
| Natural Language Processing in GIScience Applications | PySAL and Spatial Statistics Libraries |
| Machine Learning Programming for GIS | R for Geospatial Analysis & Mapping |
| Linear Programming and GIS | Javascript for GIS |
| GIS and Parallel Programming | SQL Languages for GIS |
| Object-oriented Programming in GIS Applications | GDAL/OGR and IO Libraries |
| Application Development | |
| Development Tools | Design, Development, Testing, and Deployment of GIS Applications |
| Visual Programming for GIS Applications | Verification & Validation of GIS Applications |
| SpatialMPI: Message Passage Interface for GIS Applications | Commercialization of GIS Applications |
| GIS APIs | Licensing of GIS Applications |
| Open Source Software Development | |
| Platform Specific Programming | |
| GIS and GPU Programming | |
| Programming of Mobile GIS Applications | |
| Web GIS Programming |
PD-10 - Natural Language Processing in GIScience Applications
Natural Language Processing (NLP) has experienced explosive growth in recent years. While the field has been around for decades, recent advances in NLP techniques as well as advanced computational resources have re-engaged academics, industry, and the general public. The field of Geographic Information Science has played a small but important role in the growth of this domain. Combining NLP techniques with existing geographic methodologies and knowledge has contributed substantially to many geospatial applications currently in use today. In this entry, we provide an overview of current application areas for natural language processing in GIScience. We provide some examples and discuss some of the challenges in this area.